---
license: apache-2.0
---

# Camera Angle

This model predicts an image's cinematic camera angle [low, neutral, high, overhead, dutch].  The model is a DinoV2 with registers backbone (initiated with `facebook/dinov2-with-registers-large` weights) and trained on a diverse set of two thousand human-annotated images.

## How to use:
```python

import torch
from PIL import Image
from transformers import AutoImageProcessor
from transformers import AutoModelForImageClassification

image_processor = AutoImageProcessor.from_pretrained("facebook/dinov2-with-registers-large")
model = AutoModelForImageClassification.from_pretrained('aslakey/camera_angle')
model.eval()

# example dutch angle image
# model labels [low, neutral, high, overhead, dutch]
image = Image.open('dutch_angle.jpg')
inputs = image_processor(image, return_tensors="pt")
with torch.no_grad():
    outputs = model(**inputs)

# technically multi-label training, but argmax works too!
predicted_label = outputs.logits.argmax(-1).item()
print(model.config.id2label[predicted_label])
```

## Performance:

| Camera Angle | Precision | Recall |
|--------------|-----------|--------|
| Low          | 72%       | 91%    |
| Neutral      | 86%       | 70%    |
| High         | 87%       | 75%    |
| Overhead     | 67%        | 70%     |
| Dutch (low coverage)       | 50%      | 50%    |